Analysing the cell transcriptional profile at the single-cell resolution

bioinfo-trends
sequencing-technologies
Author

Iara Souza

Published

February 29, 2024

Single-cell RNA-seq analysis is a powerful technique used in biology and medicine to study the gene expression of individual cells within a population. Single-cell gene expression analysis and bulk RNA-seq differ primarily in the scale and resolution of the analysis. Single-cell gene expression analysis focuses on individual cells, providing insights into cellular heterogeneity and rare cell populations. In contrast, bulk RNA-seq measures the average gene expression of a population of cells, masking cellular diversity. Single-cell analysis requires specialized methods to isolate and analyze individual cells, while bulk RNA-seq is more straightforward and commonly used for analyzing gene expression in larger cell populations.

Besides producing beautiful visualizations (La Manno et al. 2021), single-cell data has revolutionized the information regarding cell biology, with direct applications to the understanding of cell development and human diseases.

Single-cell graph with similarities with a map

t-SNE representation for cell types development in mouse brain. Figure from (La Manno et al. 2021).

Here’s some use cases for single-cell data:

Single-cell opened a world to new discoveries. Do you need help with analysing single-cell data? Schedule a meeting with the Lexanomics consultants!

References

La Manno, Gioele, Kimberly Siletti, Alessandro Furlan, Daniel Gyllborg, Elin Vinsland, Alejandro Mossi Albiach, Christoffer Mattsson Langseth, et al. 2021. “Molecular Architecture of the Developing Mouse Brain.” Nature 596 (7870): 92–96. https://doi.org/10.1038/s41586-021-03775-x.